Azure Recognized as an NVIDIA Cloud Exemplar, Setting the Bar for AI Performance in the Cloud

Microsoft

Feb 18, 2026

As AI models continue to scale in size and complexity, cloud infrastructure must deliver more than theoretical peak performance. What matters in practice is reliable, end-to-end, workload-level AI performance—where compute, networking, system software, and optimization work together to deliver predictable, repeatable results at scale. This directly translates to business value: efficient full-stack infrastructure accelerates time-to-market, maximizes ROI on GPU and cloud investments, and enables organizations to scale AI from proof-of-concept to revenue-generating products with predictable economics.

Today, Microsoft is proud to share an important milestone in partnership with NVIDIA: Azure has been validated as an NVIDIA Exemplar Cloud, becoming the first cloud provider recognized for Exemplar-class AI performance aligned with GB300-class (Blackwell generation) systems.
This recognition builds on Azure’s previously validated Exemplar status for H100 training workloads and reflects NVIDIA’s confidence in Azure’s ability to extend that rigor and performance discipline into the next generation of AI platforms.

What Is NVIDIA Exemplar Cloud?

The NVIDIA Exemplar Cloud initiative celebrates cloud platforms that demonstrate robust end-to-end AI workload performance using NVIDIA’s Performance Benchmarking suite.

Rather than relying on synthetic microbenchmarks, Performance Benchmarking evaluates real AI training workloads using:

Large-scale LLM training scenarios
Production-grade software stacks
Optimized system and network configurations
Workload-centric metrics such as throughput and time-to-train

Achieving Exemplar validation signals that a provider can consistently deliver world-class AI performance in the cloud, showcasing that end users are getting optimal performance value by default.

Proven Exemplar Validation on H100

Azure’s Exemplar Cloud journey began with publicly shared benchmarking results for H100-based training workloads, where Azure ND GPU clusters demonstrated exemplar performance using NVIDIA Performance Benchmarking recipes.

Those results—published previously and validated through NVIDIA’s benchmarking framework—established a proven foundation of end-to-end AI performance for large-scale, production workloads running on Azure today.

Extending Exemplar-Class AI Performance to GB300-Class Platforms

Building on the rigor and learnings from H100 validation, Microsoft has now been recognized by NVIDIA as the first cloud provider to achieve Exemplar-class performance and readiness aligned with GB300-class systems.

This designation reflects NVIDIA’s assessment that the same principles applied to H100—including end-to-end system tuning, networking optimization, and software alignment—are being successfully carried forward into the Blackwell generation.

Rather than treating GB300 as a point solution, Azure approaches it as a continuation of a proven performance model: delivering consistent world-class AI performance in the cloud while preserving the flexibility, elasticity, and global scale customers expect.

What Enables Exemplar-Class AI Performance on Azure

Delivering Exemplar-class AI performance requires optimization across the full AI stack:

Infrastructure and Networking

High-performance Azure ND GPU clusters with NVIDIA InfiniBand
NUMA-aware CPU, GPU, and NIC alignment to minimize latency
Tuned NCCL communication paths for efficient multi-GPU scaling

Software and System Optimization

Tight integration with NVIDIA software, including Performance Benchmarking recipes and NVIDIA AI Enterprise
Parallelism strategies aligned with large-scale LLM training
Continuous tuning as models, workloads, and system architectures evolve

End-to-End Workload Focus

Measuring real training performance, not isolated component metrics
Driving repeatable improvements in application-level throughput and efficiency
Closing the performance gap between cloud and on-premises systems—without sacrificing manageability

Together, these capabilities enabled Azure to deliver consistent Exemplar-class AI performance across generations of NVIDIA platforms.

What This Means for Customers

For customers training and deploying advanced AI models, this milestone delivers clear benefits:

World-class AI performance in a fully managed cloud environment
Predictable scaling from small clusters to thousands of GPUs
Faster time to train and improved performance per dollar
Confidence that Azure is ready for Blackwell-class and GB300-class AI workloads

As AI workloads become more complex and reasoning-heavy, infrastructure performance increasingly determines outcomes. Azure’s NVIDIA Cloud Exemplar recognition provides a clear signal: customers can build and scale next-generation AI systems on Azure without compromising on performance.